/PEBAL

Official code for 'Pixel-wise Energy-biased Abstention Learning for Anomaly Segmentationon Complex Urban Driving Scenes' [ECCV 2022]

Primary LanguagePython

PEBAL

PWC PWC PWC PWC

Pixel-wise Energy-biased Abstention Learning for Anomaly Segmentation on Complex Urban Driving Scenes

by Yu Tian*, Yuyuan Liu*, Guansong Pang, Fengbei Liu, Yuanhong Chen, Gustavo Carneiro.

Accepted at ECCV 2022.

Screen Shot 2022-06-11 at 2 56 11 pm

Installation

Please install the dependencies and dataset based on this installation document.

Getting start

Please follow this instruction document to reproduce our results.

Acknowledgement & Citation

The code is partially borrowed from CPS. Many thanks for their great work.

If you find this repo useful for your research, please consider citing our paper:

@misc{tian2021pixelwise,
      title={Pixel-wise Energy-biased Abstention Learning for Anomaly Segmentation on Complex Urban Driving Scenes}, 
      author={Yu Tian and Yuyuan Liu and Guansong Pang and Fengbei Liu and Yuanhong Chen and Gustavo Carneiro},
      year={2021},
      eprint={2111.12264},
      archivePrefix={arXiv},
      primaryClass={cs.CV}
}